def _BSBEC_add_met_data(self, data, met_data, years):
uids = misc.uniq_key(data, formats.UID)
for uid in uids:
for year in years:
fll_reader = FLLReader(Location(Location.BSBEC, year))
emergence = fll_reader.get_plot_fll(uid)
max_date = datetime(year + 1, 3, 10)
subset = [
x for x in data
if in_season_uid(x, uid, emergence, max_date)
]
met_data_subset = [
x for x in met_data if in_season(x, emergence, max_date)
]
accumulator = MetDataAccumulator(emergence, met_data_subset,
self._t_base)
for entry in subset:
met_entry = accumulator.get_record(entry[formats.DATE])
entry[formats.DD] = met_entry[formats.DD]
entry[formats.PAR] = met_entry[formats.PAR]
entry[formats.RAINFALL] = met_entry[formats.RAINFALL]
return data
def _fix_fll_reader(self, condition, **kwargs):
if condition['year'] > 2014:
location = Location(kwargs['location'], condition['year'])
fll_reader = FLLReaderMissing(location)
return {'fll_reader': fll_reader}
else:
return dict()
def get_fll_date(self, condition):
"""
This function gives the FLL info to the CDModel class,
to be used in simulations"""
geno = condition[formats.GENOTYPE]
year = condition['year']
fll_reader = FLLReader(Location(self._location_name, year))
return fll_reader.get_genotype_fll(geno)
def _simulate(self, keep_all=False):
years = set([x[formats.DATE].year for x in self._test_data])
genotypes = set([x[formats.GENOTYPE] for x in self._test_data])
conditions = []
for year in years:
for genotype in genotypes:
condition = {formats.GENOTYPE: genotype, 'year': year}
conditions.append(condition)
for condition in conditions:
all_params = self._model.get_parameters()
params = [
x for x in all_params
if x['conditions'] == condition[formats.GENOTYPE]
]
kwargs = dict()
keys = ['k', 'LER', 'RUE']
for key in keys:
kwargs[key] = next(x['parameter'] for x in params
if x['variable'] == key)
# hack to fix EMI-11 k value for 2012 and later
# that applies just to paper_no_training scenario
if self._model._scenario == ChrisDaveyModel.PAPER_NO_TRAINING and \
condition[formats.GENOTYPE] == "EMI-11" and \
condition[formats.YEAR] >= 2012:
kwargs['k'] = 0.5533
if condition['year'] > 2014:
location = Location(Location.BSBEC, condition['year'])
kwargs['fll_reader'] = FLLReaderMissing(location)
simulation = self._model.simulate(condition, t_base=0, **kwargs)
for entry in self._test_data:
match = [
x for x in simulation
if x[formats.GENOTYPE] == entry[formats.GENOTYPE]
and x[formats.DATE] == entry[formats.DATE]
]
if len(match) > 1:
# this should not happen
raise Exception("How does that even?!")
elif len(match) == 1:
entry['predicted'] = match[0][formats.DW_PLANT]
if keep_all:
for var_name in [
formats.PAR, formats.DD,
formats.LEAF_AREA_INDEX
]:
entry[var_name] = match[0][var_name]
def _fix_start_date(self, years, genotype):
start_dates = []
for year in years:
location = Location(self._location.get_name(), year)
fll_reader = FLLReader(location)
fll_date = fll_reader.get_genotype_fll(genotype)
start_dates.append(int(fll_date.strftime("%j")))
jul = sum(start_dates) / len(start_dates)
date_string = '%d %s' % (jul, self._location.get_year())
start_date = datetime.strptime(date_string, "%j %Y")
return start_date
def _inject_fll(self, data, preps=[], additional_phenos=False):
# inject at FLL
uids = misc.uniq_key(data, formats.UID)
years = set([x[formats.DATE].year for x in data])
for year in years:
reader = FLLReader(Location(Location.BSBEC, year))
for uid in uids:
fll_date = reader.get_plot_fll(uid)
entry = {
formats.UID: uid,
formats.DATE: fll_date,
formats.GENOTYPE: misc.assign_geno_bsbec(uid),
formats.TRANSMISSION: 1.0,
formats.DD: 0.0,
formats.PAR: 0.0,
formats.LEAF_AREA_INDEX: 0.0,
formats.STEM_COUNT: 0.0,
formats.CANOPY_HEIGHT: 0.0,
formats.DW_PLANT: 0.0
}
if additional_phenos:
if year < 2016:
diam = None
else:
diam = 0
entry[formats.BASE_DIAM_1] = diam
entry[formats.BASE_DIAM_2] = diam
entry[formats.STEM_DIAM] = diam
entry[formats.YEAR] = year
entry = misc.row_col_BSBEC(entry)
entry[formats.DOY] = int(
entry[formats.DATE].strftime("%j"))
entry[formats.FLOWERING_SCORE] = 0
entry[formats.RAINFALL] = 0
if preps != []:
for prep in preps:
new_entry = deepcopy(entry)
new_entry[formats.PSEUDO_REP] = prep
data.append(new_entry)
else:
data.append(entry)
return data
def get_met_data(self, condition, t_base):
location = Location(self._location_name, condition['year'])
met_data = MetDataReaderCSV(location, t_base=t_base).get_records()
return met_data
def _create_locations(self, years, location_name):
locations = []
for year in years:
locations.append(Location(location_name, year))
return locations
def create_locations(self, years):
locations = []
for year in years:
locations.append(Location(Location.BSBEC, year))
return locations